Video Annotation for Building Damage Detection

Client's Challenge & Our Solution

A leading construction and infrastructure firm needed to develop a model for detecting damage on the exterior surfaces of buildings using aerial video footage captured by drones. The client had captured high-resolution aerial videos of buildings from various angles but required detailed and accurate annotations to train their AI model. Their primary challenge was to identify and label damages such as cracks, dents, water stains, corrosion, and other surface irregularities using polygon annotations.

FutureBeeAI stepped in to provide a comprehensive solution by performing precise polygon annotation for each visibly damaged area in the aerial videos. Our team worked and annotated around 100000 frames and annotated each damage accurately. With our expertise in polygon annotation and AI training data preparation, we helped the client create a high-quality, structured dataset suitable for their damage detection model.

Outcome & Features:

We annotated 100000 frames with our proprietary annotation platform

We labeled various defects like cracks, dents, water stains, and corrosion

We prepared the entire dataset within 12 weeks as per the client's timeline